Decision Making

Knight's distinction is clean and consequential: risk is measurable probability; uncertainty is not. Insurance handles risk; entrepreneurship handles uncertainty. Profit exists precisely because some situations cannot be…

Simon's 1947 book is one of the foundational texts of modern management theory — the argument that real organisations make decisions through bounded rationality rather than the idealised comprehensive rationality of clas…

The companion paper to Simon's books already in the library. Here Simon argues that complex systems evolve faster when they are hierarchically modular — "nearly decomposable" — because subsystems can evolve independently…

Damasio's central discovery is that patients with damage to the emotional centres of the brain do not become more rational — they become unable to decide at all. Emotion is not noise in the decision-making process; it is…

The basic grammar of systems: stocks, flows, feedback loops, leverage points. Meadows teaches you to stop asking "who caused this" and start asking "what structure produces this behaviour" — the single most useful shift…

Kahneman's life's work compressed into one book: the distinction between System 1 (fast, automatic, intuitive) and System 2 (slow, deliberate, effortful), and the systematic biases that arise when System 1 handles questi…

Lewis's book is a popular treatment of the psychology of impulsive behaviour — why we make purchases we did not plan, choose options we will regret, click on things we did not mean to click on. The research it summarises…

Duke, a former professional poker player turned decision-science teacher, argues that the quality of a decision and the quality of its outcome are different things, and that treating them as the same is the single most e…

Miozzi addresses a gap in price theory that matters for product strategy: if markets are always in motion, what do current prices actually tell us? The Austrian school insight is that disequilibrium prices carry differen…

Munger's collected speeches, essays, and conversations on mental models, multidisciplinary thinking, and the psychology of human misjudgment, edited by Peter Kaufman. The Stripe Press expanded edition is the definitive v…

Peterson frames a problem that most AI governance literature ignores: compliance layers built to make algorithmic decisions reviewable can also be gamed by successive administrations who learn to satisfy the form of over…

Falk and Tsoukalas construct a task-based competitive model to show that the real problem with AI-driven displacement is not ignorance but a classic collective action failure: each firm rationally automates while the agg…

The authors reframe what looks like a labor market reform as something fundamentally different: a platform-mediated private market for intangible assets. This distinction matters because it explains why standard wage-set…

Gigerenzer has spent four decades dismantling the assumption that rational decision-making means maximising expected utility, and this paper reads as a late summation of that project — a direct engagement with Simon's le…

The paper's central finding is unsettling in a precise way: giving users the ability to edit AI reasoning increases their sense of control but also increases over-reliance when the AI is wrong — an illusion of control th…

Aral (MIT, one of the most cited scholars in digital economics) and Caosun construct a formal dynamic model that makes precise what practitioners sense but cannot yet argue: AI adoption can be individually rational at ev…

This paper addresses a fundamental challenge for product directors building AI-powered products: how do users develop trust and delegation strategies when the same AI system performs differently across different tasks? T…

Palminteri and Wyart have established themselves as a productive collaboration in the library's decision-making research, with their previous work scoring 8 for bringing computational insights to human judgment under unc…

Palminteri and Wyart's analysis of pathological decision-making reveals the computational foundations beneath everyday judgment by examining what happens when these systems fail. Their focus on Bayesian inference breakdo…

Palminteri and Wyart tackle the fundamental question of how technology changes who makes decisions and how. Their framework distinguishing behavioural analysis, nudging, and boosting offers product leaders a vocabulary f…

Palminteri and Wyart, whose empirical work on decision-making under uncertainty already enriches this library, here tackle the foundational question of what decision science actually is as a discipline. For product direc…

The intersection of statistical decision theory with perception and cognition offers product directors a rigorous framework for understanding how people actually process information and make choices — not the rational ac…